• 제목/요약/키워드: Cluster Analysis(CA)

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주성분 분석 및 군집분석을 이용한 지역정보 유형화 프레임워크의 설계와 구현 (Effective Classification Framework Design and Implementation for Rural Regional Information using Principal Component Analysis and Cluster Analysis)

  • 서교;김태곤;이지민;이정재
    • 한국농공학회논문집
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    • 제54권1호
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    • pp.73-81
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    • 2012
  • For planning and developing rural regions, it is very important to understand and utilize regional characteristics including social, demographic, and economic aspects. The purpose of this study is to find effective analysis techniques and provide a procedure design for mining regional characteristics in South Korea through reviewing and analyzing 41 related studies. The engaged research methods can be classified into five categories (PCA+CA, PCA, CA, GIS, and PCA+GIS) with the combination of three methodologies: principal component analysis (PCA), cluster analysis (CA), and geographical information system (GIS). The combination of PCA and CA occupied about 40 % of research methods used in related studies. The analysis tool of Korean Rural Information Supporting System (KRISS) is designed based on the outcomes of this study and applied to classify the regional capacity of agriculture using agricultural census data (2000) for evaluating its applicability.

대학 강의평가에서 문항 추출에 관한 연구 (A Study on Effective Selection of University Lecture Evaluation)

  • 황세명;김인택
    • 공학교육연구
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    • 제8권1호
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    • pp.31-45
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    • 2005
  • 본 논문에서는, 강의 평가에 필요한 설문을 효과적이며 체계적으로 얻기 위한, 대표 문항 추출 방법을 비교하였다. 비교에 사용한 방법은 요인분석(Factor Analysis: FA), FCM(Fuzzy c-Means) 알고리즘과 군집분석(Cluster Analysis : CA) 등으로 이러한 방법들을 사용하여 고려할 수 있는 다양한 형태의 많은 문항들로부터 적은 수의 문항을 추출한다. 추출된 문항은 많은 수의 문항들이 형성하는 클러스터의 대표 문항을 이루고 있다. 이를 위해 여러 개의 설문지로부터 얻은 120 문항의 강의 평가서를 명지대학교 외 3 개 대학교 646명의 학생들에게 평가를 실시하여 데이터를 얻었는데 학생들은 주어진 문항에 대하여 "매우 그렇다", "그렇다", "보통이다", "그렇지 않다", "매우 그렇지 않다", 그리고 "해당 없다"까지의 6등급으로 응답하였다. 각 문항에 대한 학생들의 응답 성향을 분석하여 약 25문항을 추출하였다. 실험 결과 본 논문에서 비교 분석한 요인분석, FCM알고리즘과 군집분석 등의 기법은 매우 유사한 설문을 추출할 수 있었다.

무주지역 수질특성자료의 통계학적 분석에 의한 소유역 구분 (Watershed Classification Using Statistical Analysis of water Quality Data from Muju area)

  • 한원식;우남칠;이기철;이광식
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제7권3호
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    • pp.19-32
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    • 2002
  • 본 연구는 무주군 적상산 부근에 위치하는 소유역에서 지표수의 수질과 인접한 천층지하수 수질사이의 관계 및 지질매체와 오염원의 유입에 의한 계절적인 변동을 규명하기 위하여 수행되었다. 8월과 10월 두 차례의 조사결과 이곳 지표수와 지하수 수질은 Ca-$HCO_3$유형이 주를 이루고 있었으며 인근 광산부근에서는 중금속에 의한 오염이 나타나고 있었다. 10월 조사시에 인가가 밀집한 지역에서는 질산성 질소의 의한 오염 또한 높게 나타나는 특징을 보이고 있다. 이러한 자료를 토대로 군집분석(Cluster Analysis)과 주성분 분석(Principal Component Analysis)을 실시하였으며, 군집분석결과 지표수는 5개의 그룹으로 구분되었고 지하수는 3개의 그룹으로 구분되었다. 주성분분석 결과는 군집분석 시에 나타난 결과를 효과적으로 지지하고 있으며 (1)지질매체의 수리지화학적 반응, (2)오염물질의 유입 (3) 인근광산에 의한 중금속 오염이 복합적으로 반응하여 나타난 결과로 해석된다.

전자코를 이용한 두부의 저장특성 분석 주성분 분석과 군집분석을 이용하여 - (Characteristics of Shelf-life of Soybean Curd by Electronic Noses - Using PCA and cluster analysis)

  • 김성민;노봉수
    • Journal of Biosystems Engineering
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    • 제27권3호
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    • pp.241-248
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    • 2002
  • An electronic noses system including six metal oxide sensors was used to predict the characteristics of shelf-life of soybean curd. Soybean curd was stored at two different temperatures defined as low temperature(5$\^{C}$) and high temperature(25$\^{C}$). Resistance changes of the sensors were measured 13 times for 19 days at low temperature and 19 times for 120 hours at high temperature. Three different analytical methods such as graphical analysis(GA), principal component analysis(PCA), and cluster analysis(CA) were used to analyze sensors outputs. The ratio of resistance was decreased according to increasement of shelf-life. Using PCA it was possible to predict freshness and shelf-life time of soybean curds. Also, using CA it was possible to simplify an electronic nose system. Electronic nose system could be an efficient method to predict shelf-life and to evaluate quality in foods.

다변량통계분석 및 유역환경모델을 이용한 금호강 중·상류 유역의 수질특성평가 (Assessment of Water Quality Characteristics in the Middle and Upper Watershed of the Geumho River Using Multivariate Statistical Analysis and Watershed Environmental Model)

  • 서영민;권구호;최윤영;이병준
    • 한국물환경학회지
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    • 제37권6호
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    • pp.520-530
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    • 2021
  • Multivariate statistical analysis and an environmental hydrological model were applied for investigating the causes of water pollution and providing best management practices for water quality improvement in urban and agricultural watersheds. Principal component analysis (PCA) and cluster analysis (CA) for water quality time series data show that chemical oxygen demand (COD), total organic carbon (TOC), suspended solids (SS) and total phosphorus (T-P) are classified as non-point source pollutants that are highly correlated with river discharge. Total nitrogen (T-N), which has no correlation with river discharge and inverse relationship with water temperature, behaves like a point source with slow and consistent release. Biochemical oxygen demand (BOD) shows intermediate characteristics between point and non-point source pollutants. The results of the PCA and CA for the spatial water quality data indicate that the cluster 1 of the watersheds was characterized as upstream watersheds with good water quality and high proportion of forest. The cluster 3 shows however indicates the most polluted watersheds with substantial discharge of BOD and nutrients from urban sewage, agricultural and industrial activities. The cluster 2 shows intermediate characteristics between the clusters 1 and 3. The results of hydrological simulation program-Fortran (HSPF) model simulation indicated that the seasonal patterns of BOD, T-N and T-P are affected substantially by agricultural and livestock farming activities, untreated wastewater, and environmental flow. The spatial analysis on the model results indicates that the highly-populated watersheds are the prior contributors to the water quality degradation of the river.

분산주성분 분석을 이용한 실내환경 중 PM-10 오염의 패턴분류 (Pattern Classification of PM -10 in the Indoor Environment Using Disjoint Principal Component Analysis)

  • 남보현;황인조;김동술
    • 한국대기환경학회지
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    • 제18권1호
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    • pp.25-37
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    • 2002
  • The purpose of the study was to survey the distribution patterns of inorganic elements of PM-10 in the various indoor environments and analyze the pollution patterns of aerosol in various places of indoor environment using a pattern recognition method based on cluster analysis and disjoint principal component analysis. A total of 40 samples in the indoor had been collected using mini-vol portable samplers. These samples were analyzed for their 19 bulk inorganic compounds such as B, Na, Mg, Al, K, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, and Pb by using an ICP-MS. By applying a disjoint principal component analysis, four patterns of the indoor air pollutions were distinguished. The first pattern was identified as a group with high concentrations of PM-10, Na, Mg, and Ca. The second pattern was identified as a group with high concentrations B, Mg, At, Ca, Fe, Cu, and Ba. The third pattern was a group of sites with high concentrations of K, Zn. Cd. The fourth pattern was a group with low concentrations PM-10 and all inorganic elements. This methodology was found to be helpful enough to set the criteria standard of indoor air quality, corresponding pollutants, and classification of indoor environment categories when making an indoor air quality law.

WITNESSING DISSOLUTION OF A STAR CLUSTER IN THE SEXTANS DWARF GALAXY

  • Kim, Hak-Sub;Han, Sang-Il;Joo, Seok-Joo;Yoon, Suk-Jin
    • 천문학회보
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    • 제43권1호
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    • pp.32.3-32.3
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    • 2018
  • We report a possible discovery of a relic of a dissolved star cluster in the Sextans dwarf spheroidal galaxy. Using the hk index (${\equiv}$(Ca-b)-(b-y)) as a photometric metallicity indicator, we have successfully discriminated the metal-poor and metal-rich stars in the galaxy and found an unexpected number density peak of metal-poor stars near the galaxy center. The analysis of color-magnitude diagrams reveals that they appear to be originated from an old, metal-poor globular cluster which might be slightly farther than the bulk of field stars in the galaxy. This supports the presence of the star cluster remnants in the galaxy which have been suggested by previous studies. If confirmed, dissolution of a star cluster provides a piece of evidence of a cored dark-matter halo profile for the Sextans dwarf galaxy.

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Mineral Compositions of Korean Wheat Cultivars

  • Choi, Induck;Kang, Chon-Sik;Hyun, Jong-Nae;Lee, Choon-Ki;Park, Kwang-Geun
    • Preventive Nutrition and Food Science
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    • 제18권3호
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    • pp.214-217
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    • 2013
  • Twenty-nine Korean wheat cultivars were analyzed for 8 important minerals (Cu, Fe, Mn, Zn, Ca, K, Mg and P) using Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). A hierarchical cluster analysis (HCA) was applied to classify wheat cultivars, which has a similarity in mineral compositions. The concentration ranges of the micro-minerals Cu, Fe, Mn, and Zn: 0.12~0.71 mg/100 g, 2.89~5.89 mg/100 g, 1.65~4.48 mg/100 g, and 2.58~6.68 mg/100 g, respectively. The content ranges of the macro-minerals Ca, K, Mg and P: 31.3~46.3 mg/100 g, 288.2~383.3 mg/100 g, 113.6~168.6 mg/100 g, and 286.2~416.5 mg/100 g, respectively. The HCA grouped 6 clusters from all wheat samples and a significant variance was observed in the mineral composition of each group. Among the 6 clusters, the second group was high in Fe and Ca, whereas the fourth group had high Cu, Mn and K concentrations; the fifth cluster was high in Zn, Mg and P. The variation in mineral compositions in Korean wheat cultivars can be used in the wheat breeding program to develop a new wheat cultivar with high mineral content, thus to improve the nutritional profile of wheat grains.

울릉도 나리분지의 산림군락과 환경요인과의 상관관계 (Correlation Analysis between Forest Community and Environment Factor of Nari Basin in Ulleung Island)

  • 정재민;윤준혁;신재권;문현식
    • 농업생명과학연구
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    • 제45권3호
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    • pp.1-7
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    • 2011
  • 본 연구는 울릉도 나리분지의 군락구조와 환경요인의 상관관계를 파악하여 산림식생의 보전 및 관리에 필요한 생태학적 기초자료를 제공하기 위하여 수행되었다. 나리분지의 산림군락은 너도밤나무군락, 당마가목군락, 소나무군락, 풍게나무군락, 두메오리나무군락으로 분류되었다. DCCA 분석 결과, 환경요인 중 해발이 군집의 분포에 영향을 미치는 인자인 것으로 나타났다. 너도밤나무군락과 당마가목군락은 방위, Na, C/N의 환경요인과 군락단위의 분포지가 높은 상관관계를 나타내었다. 풍게나무군락은 Ca, K 등과 상관관계가 높은 것으로 나타났으며, 두메오리나무군락은 CEC의 함량이 높은 입지에 분포하고 있었으며, 해발고와 높은 상관관계가 있었다. 소나무군락은 Ca, CEC의 함량이 높은 입지에 분포하는 것으로 나타났다.

다변량분석법을 활용한 농업용 저수지 수질유형분류 (Classification of Agricultural Reservoirs Using Multivariate Analysis)

  • 최은희;김형중;박영석
    • 한국관개배수논문집
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    • 제17권2호
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    • pp.17-27
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    • 2010
  • In order to manage the water quality in reservoir, it is necessary to understand the temporal and spatial variation of reservoirs and to classify the reservoirs. In this research, agricultural reservoirs are classified according to physical characteristics (depth, residence time, shape of the reservoir etc) and water quality using multivatriate analysis (PCA and CA). CA (Cluster Analysis) method classify reservoirs into several groups as a similarity of the reservoirs, but it is difficult to indicate a full list to the one table. In case of PCA (Principle Component Analysis) method, it has the advantage for the classification on the reservoirs depending on the water quality similarity and also it is useful to analyze the relationship between related factors through correlation analysis. However PCA is limited to classify into several groups based on the characteristics of the reservoirs and each user should be classified as randomly subjective according to the relative position of the reservoir in the figure. In conclusions, compared to conventional reservoirs classification methods, both CA and PCA methods are considered to be a classification method that describes the nature of the reservoir well, but classification results has a restriction on use, so further research will be needed to complement.

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